Presenting video content to online system users in response to user interactions with video content presented in a feed of content items

ABSTRACT

An online system generates a feed of content items for a user subject to a limitation restricting the number of content items including video data (“video content items”) included in the feed. If the user interacts with a video content item the feed, the online system selects candidate video content items based on characteristics of the video content item in the feed and characteristics of the user. The online system determines likelihoods of the user interacting with various candidate video content items and selects candidate video content items based on the determined likelihoods. To present the user with additional video content items, the online system generates an interface including the selected candidate video content items and presents the interface to the user. The interface may be presented in place of the feed or may be presented as within the feed and presents different video content items based on user interactions.

BACKGROUND

This disclosure relates generally to online systems, and morespecifically to presenting video content to users of an online system.

An online system allows users to connect to and to communicate withother users of the online system. Users create profiles on an onlinesystem that are tied to their identities and include information aboutthe users, such as interests and demographic information. The users maybe individuals or entities such as corporations or charities. An onlinesystem receives content from various sources, such as users andadvertisers, and selects content items from the received content forpresentation to its users. The online system presents content items tovarious users by the online system to encourage user interaction withthe online system.

Many online systems present content items to their users via a feed ofcontent items (e.g., a newsfeed). For example, an online system presentsa newsfeed to a user that includes advertisements, stories describingactions performed by additional users of the online system connected tothe user, and content provided to videos posted by additional users ofthe online system connected to the user. To diversify content presentedto the user via a feed of content, an online system may enforcelimitations on types of content presented in a feed of content item. Forexample, an online system limits a total number of video content itemsincluded in a feed of content items or limits a number of video contentitems having certain characteristics included in a feed of contentitems.

If a user of an online system interacts with a video content itempresented in a feed, an online system may infer the user has an interestin additional video content items, such as video content items havingsimilar characteristics to the video content item with which the userinteracted. While the online system may identify additional contentitems having matching or similar characteristics to the video contentitem with which the user interacted, enforcing limitations on the numberof video content items included in the feed may prevent a conventionalonline system from including the identified additional content items inthe feed. Omitting the additional video content items from the feed mayreduce user interaction with the feed, which may impair subsequentselection of content for presentation to the user by the online system.

SUMMARY

An online system generates a feed of content items for presentation to auser, such as a newsfeed including content items. The feed may includevarious types of content items, such as content items including videodata (“video content items”) and content items including text or imagedata. In some embodiments, the online system limits a number of videocontent items included in the feed. For example, the online systemincludes less than a threshold number of video content items in the feedor includes less than a threshold number of video content items havingspecific characteristics in the feed. As a specific example, the onlinesystem includes no more than five video content items provided by usersin a feed and includes no more than three video content items that areadvertisements in the feed.

To allow a user presented with the feed to view additional video contentitems while enforcing one or more limitations on the number of videocontent items included in the feed, the online system, when a userpresented with the feed interacts with a video content item in the feed,the online system generates an interface including additional videocontent items and presents the interface to the user. The interfaceincluding the additional video content items may be generated inresponse to the user performing certain types of interactions with avideo content item presented in the feed. Example interactions with avideo content item causing the online system to generate the interfaceinclude: requesting to view the video data in the video content item,unmuting the video in the video data in the video content item, playingthe video data in the video content item in a full-screen mode, andviewing at least a threshold percentage of the video data.

When generating the interface, the online system identifies candidatevideo content items having that have at least a threshold number ofcharacteristics matching characteristics of a video content item withwhich the user interacted or having at least a threshold number ofcharacteristics matching characteristics of the user. For example, theonline system identifies video content items provided to the onlinesystem by a user who provided the video content item with which the userinteracted as candidate video content items. As another example, theonline system identifies candidate video content items as video contentitems including text data (e.g., keywords, hashtags) matching (orassociated with) text data included in the video content item with whichthe user interacted.

In various embodiments, one or more candidate video content items havingcharacteristics matching at least a threshold number of characteristicsassociated with the user are identified. As an example, video contentitems associated with a geographic location (or other demographicinformation) matching a geographic location (or other demographicinformation) associated with the user are identified as candidate videocontent items. For example, candidate video content items are identifiedas video content items that are associated with an interaction or actionthat is also associated with the user (e.g., video content itemsassociated with a prior search performed by the user via the onlinesystem). As another example, video content items having at least athreshold measure of similarity to video content items with which theuser previously interacted are identified as candidate content items(e.g., video content items having at least a threshold number ofcharacteristics matching characteristics of the video content item withwhich the user interacted). Candidate video content items may also beidentified as video content items associated with the video content itemwith which the viewing user interacted (e.g., additional video contentitems posted in comments to the video content item, additional videocontent items manually linked to the video content item, additionalvideo content items associated with one or more actions performed by theuser on a third party system and communicated to the online system,etc.). Characteristics of the user may include measures of similaritybetween the user and additional users of the online system. For example,the online system generates a measure of similarity between a user andan additional user based on matching or similar characteristics of theuser and the additional user, content with which the user and theadditional user interacted, or other suitable information. Video contentitems with which additional users having at least a threshold measure ofsimilarity to the user interacted are identified as candidate videocontent items in some embodiments. For example, additional video contentitems with which additional users having at least a threshold measure ofsimilarity to the user and who performed a specific action (e.g., postedthe additional video content item to the online system, shared theadditional video content item with another user, viewed video data inthe additional video content item, commented on the additional videocontent item etc.) are identified as candidate video content items.

The online system determines likelihoods of the user interacting withvarious candidate video content items based on characteristics of theuser, characteristics of content with which the user previouslyinteracted, and characteristics of the candidate video content items.For example, the online system determines a likelihood of the userinteracting with each candidate video content item. The online systemmay determine the likelihood of the user interacting with a candidatevideo content item based on the user's prior interactions with contentitems having at least a threshold number of characteristics matching orsimilar to characteristics of the candidate video content item,interactions by additional users connected to the user with thecandidate video content item, based on interactions by additional usershaving at least a threshold measure of similarity to the user with thecandidate video content item, or based on any other suitableinformation. In some embodiments, the online system trains amachine-learned model to determine likelihoods of user interacting withcandidate video content items (e.g., based on historical interactions ofusers connected to the viewing user with the video content items, basedon prior interactions by the user, based on demographic informationassociated with the user, etc.). Characteristics of the candidatecontent item may also be used when determining the likelihoods of theuser interacting with various candidate content items.

Based at least in part on the likelihoods of the user interacting withcandidate video content items, the online system selects one or morecandidate video content items. For example, the online system ranks thecandidate video content items based on the likelihoods of the userinteracting with the candidate video content items and selects candidatevideo content items having at least a threshold position in the ranking.The online system generates an interface including the selectedcandidate video content items, such as an interface including one ormore of the selected candidate video content items. In some embodiments,the generated interface includes information describing one or morereasons for including the selected candidate video content items in theinterface. For example, if the user views a video content item, theinterface presented to the user includes a caption indicating thatadditional users that viewed the video content item also viewed theselected candidate video content items included in the interface.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a system environment in which an onlinesystem operates, in accordance with an embodiment.

FIG. 2 is a block diagram of an online system, in accordance with anembodiment.

FIG. 3 is a flowchart of a method for presenting additional videocontent items to an online system user responsive to receiving aninteraction by the user with a video content item presented in a contentfeed, in accordance with an embodiment.

FIGS. 4A-4C are example interfaces presenting candidate video contentitems selected for presentation to an online system user, in accordancewith an embodiment.

The figures depict various embodiments for purposes of illustrationonly. One skilled in the art will readily recognize from the followingdiscussion that alternative embodiments of the structures and methodsillustrated herein may be employed without departing from the principlesdescribed herein.

DETAILED DESCRIPTION System Architecture

FIG. 1 is a block diagram of a system environment 100 for an onlinesystem 140, such as a social networking system. The system environment100 shown by FIG. 1 comprises one or more client devices 110, a network120, one or more third-party systems 130, and the online system 140. Inalternative configurations, different and/or additional components maybe included in the system environment 100.

The client devices 110 are one or more computing devices capable ofreceiving user input as well as transmitting and/or receiving data viathe network 120. In one embodiment, a client device 110 is aconventional computer system, such as a desktop or a laptop computer.Alternatively, a client device 110 may be a device having computerfunctionality, such as a personal digital assistant (PDA), a mobiletelephone, a smartphone or another suitable device. A client device 110is configured to communicate via the network 120. In one embodiment, aclient device 110 executes an application allowing a user of the clientdevice 110 to interact with the online system 140. For example, a clientdevice 110 executes a browser application to enable interaction betweenthe client device 110 and the online system 140 via the network 120. Inanother embodiment, a client device 110 interacts with the online system140 through an application programming interface (API) running on anative operating system of the client device 110, such as IOS® orANDROID™.

The client devices 110 are configured to communicate via the network120, which may comprise any combination of local area and/or wide areanetworks, using both wired and/or wireless communication systems. In oneembodiment, the network 120 uses standard communications technologiesand/or protocols. For example, the network 120 includes communicationlinks using technologies such as Ethernet, 802.11, worldwideinteroperability for microwave access (WiMAX), 3G, 4G, code divisionmultiple access (CDMA), digital subscriber line (DSL), etc. Examples ofnetworking protocols used for communicating via the network 120 includemultiprotocol label switching (MPLS), transmission controlprotocol/Internet protocol (TCP/IP), hypertext transport protocol(HTTP), simple mail transfer protocol (SMTP), and file transfer protocol(FTP). Data exchanged over the network 120 may be represented using anysuitable format, such as hypertext markup language (HTML) or extensiblemarkup language (XML). In some embodiments, all or some of thecommunication links of the network 120 may be encrypted using anysuitable technique or techniques.

One or more third party systems 130 may be coupled to the network 120for communicating with the online system 140, which is further describedbelow in conjunction with FIG. 2. In one embodiment, a third partysystem 130 is an application provider communicating informationdescribing applications for execution by a client device 110 orcommunicating data to client devices 110 for use by an applicationexecuting on the client device. In other embodiments, a third partysystem 130 provides content or other information for presentation via aclient device 110. A third party system 130 may also communicateinformation to the online system 140, such as advertisements, content,or information about an application provided by the third party system130.

FIG. 2 is a block diagram of an architecture of the online system 140.The online system 140 shown in FIG. 2 includes a user profile store 205,a content store 210, an action logger 215, an action log 220, an edgestore 225, a content selection module 230, and a web server 235. Inother embodiments, the online system 140 may include additional, fewer,or different components for various applications. Conventionalcomponents such as network interfaces, security functions, loadbalancers, failover servers, management and network operations consoles,and the like are not shown so as to not obscure the details of thesystem architecture.

Each user of the online system 140 is associated with a user profile,which is stored in the user profile store 205. A user profile includesdeclarative information about the user that was explicitly shared by theuser and may also include profile information inferred by the onlinesystem 140. In one embodiment, a user profile includes multiple datafields, each describing one or more attributes of the correspondingonline system user. Examples of information stored in a user profileinclude biographic, demographic, and other types of descriptiveinformation, such as work experience, educational history, gender,hobbies or preferences, location and the like. A user profile may alsostore other information provided by the user, for example, images orvideos. In certain embodiments, images of users may be tagged withinformation identifying the online system users displayed in an image. Auser profile in the user profile store 205 may also maintain referencesto actions by the corresponding user performed on content items in thecontent store 210 and stored in the action log 220.

While user profiles in the user profile store 205 are frequentlyassociated with individuals, allowing individuals to interact with eachother via the online system 140, user profiles may also be stored forentities such as businesses or organizations. This allows an entity toestablish a presence on the online system 140 for connecting andexchanging content with other online system users. The entity may postinformation about itself, about its products or provide otherinformation to users of the online system 140 using a brand pageassociated with the entity's user profile. Other users of the onlinesystem 140 may connect to the brand page to receive information postedto the brand page or to receive information from the brand page. A userprofile associated with the brand page may include information about theentity itself, providing users with background or informational dataabout the entity.

The content store 210 stores objects that each represent various typesof content, so an object represents a content item. Examples of contentrepresented by an object include a page post, a status update, aphotograph, a video, a link, a shared content item, a gaming applicationachievement, a check-in event at a local business, a page (e.g., brandpage), or any other type of content. Some content items included in thecontent store 210 include video data that is presented to an onlinesystem user. A content item including video data is referred to hereinas a “video content item.” Online system users may create objects storedby the content store 210, such as status updates, photos tagged by usersto be associated with other objects in the online system 140, events,groups or applications. In some embodiments, objects are received fromthird-party applications or third-party applications separate from theonline system 140. In one embodiment, objects in the content store 210represent single pieces of content, or content “items.” Hence, onlinesystem users are encouraged to communicate with each other by postingtext and content items of various types of media to the online system140 through various communication channels. This increases the amount ofinteraction of users with each other and increases the frequency withwhich users interact within the online system 140.

The action logger 215 receives communications about user actionsinternal to and/or external to the online system 140, populating theaction log 220 with information about user actions. Examples of actionsinclude adding a connection to another user, sending a message toanother user, uploading an image, reading a message from another user,viewing content associated with another user, and attending an eventposted by another user. As an example of a communication about useraction external to the online system 140, the action logger 215 receivesinformation describing content items provided by a third party system130 accessed by an online system user or other information describinginteractions by the online system user with content provided by thethird party system 130 and information identifying the online systemuser and stores the information describing the online system user'sinteractions with content provided by the third party system in theaction log 220 in association with the online system user. For example,a third party system 130 includes a tracking mechanism, such as atracking pixel, in content provided by the third party system 130, so aclient device 110 presenting the content from the third party system 130executes instructions in the tracking mechanism when one or morespecified interactions with the content provided by the third partysystem 130 are received via the client device 110 (e.g., an interactionwith the content provided by the third party system 130 matching aninteraction specified in the tracking mechanism. For example, the actionlogger 215 logs information describing a number of times a user of theonline system 140 accessed a web page provided by a third party system130 as well as a number of times the user accessed video contentpresented via the web page provided by the third party system 130 basedon information received from a tracking mechanism included in the webpage. In addition, a number of actions may involve an object and one ormore particular users, so these actions are associated with theparticular users as well and stored in the action log 220.

Additionally, the action logger 215 logs information describinginteractions between online system users and video content itemspresented to the online system users to the action log 220. For example,the action logger 215 obtains information describing a number of times auser of the online system 140 played video data in a video content itemor commented on a video content item and logs the information in theaction log 220 along with information identifying the user. Timesassociated with the interactions between the user and the video contentitem may also be stored in the action log 220 association withinformation identifying the user and identifying the video content item.

The action log 220 may be used by the online system 140 to track useractions on the online system 140, as well as actions on third partysystems 130 that communicate information to the online system 140. Usersmay interact with various objects on the online system 140, andinformation describing these interactions is stored in the action log220. Examples of interactions with objects include: commenting on posts,sharing links, checking-in to physical locations via a client device110, accessing content items (including video content items), and anyother suitable interactions. Additional examples of interactions withobjects on the online system 140 that are included in the action log 220include: commenting on a photo album, communicating with a user,establishing a connection with an object, joining an event, joining agroup, creating an event, authorizing an application, using anapplication, expressing a preference for an object (“liking” theobject), and engaging in a transaction. Additionally, the action log 220may record a user's interactions with advertisements on the onlinesystem 140 as well as with other applications operating on the onlinesystem 140. In some embodiments, data from the action log 220 is used toinfer interests or preferences of a user, augmenting the interestsincluded in the user's user profile and allowing a more completeunderstanding of user preferences.

The action log 220 may also store user actions taken on a third partysystem 130, such as an external website, and communicated to the onlinesystem 140. For example, an e-commerce website may recognize a user ofan online system 140 through a social plug-in enabling the e-commercewebsite to identify the user of the online system 140. Because users ofthe online system 140 are uniquely identifiable, e-commerce websites,such as in the preceding example, may communicate information about auser's actions outside of the online system 140 to the online system 140for association with the user. Similarly, a third party system 130 mayinclude a tracking mechanism, such as a tracking pixel, in contentprovided by the third party system 130. The tracking mechanism includesinstructions identifying one or more interactions with the content itemand instructions that, when executed by a client device 110, communicateinformation identifying the one or more interactions to the onlinesystem 140. In some embodiments, the tracking mechanism alsocommunicates information identifying a user who performed the one ormore interactions; alternatively, the online system 140 retrievesinformation identifying the user who performed the one or moreinteractions after receiving information describing the one or moreinteractions and stores information identifying the one or moreinteractions, the content provided by the third party system 130, andthe user who performed the one or more interactions. Hence, the actionlog 220 may record information about actions users perform on a thirdparty system 130, including webpage viewing histories, interactions withadvertisements, purchases made, and other patterns from shopping andbuying. Additionally, actions a user performs via an applicationassociated with a third party system 130 and executing on a clientdevice 110 may be communicated to the action logger 215 for storing inthe action log 220 by the application for recordation and associationwith the user by the online system 140.

In one embodiment, the edge store 225 stores information describingconnections between users and other objects on the online system 140 asedges. Some edges may be defined by users, allowing users to specifytheir relationships with other users. For example, users may generateedges with other users that parallel the users' real-life relationships,such as friends, co-workers, partners, and so forth. Other edges aregenerated when users interact with objects in the online system 140,such as expressing interest in a page on the online system 140, sharinga link with other users of the online system 140, and commenting onposts made by other users of the online system 140.

In one embodiment, an edge may include various features eachrepresenting characteristics of interactions between users, interactionsbetween users and objects, or interactions between objects. For example,features included in an edge describe a rate of interaction between twousers, how recently two users have interacted with each other, a rate oramount of information retrieved by one user about an object, or numbersand types of comments posted by a user about an object. The features mayalso represent information describing a particular object or user. Forexample, a feature may represent the level of interest that a user hasin a particular topic, the rate at which the user logs into the onlinesystem 140, or information describing demographic information about theuser. Each feature may be associated with a source object or user, atarget object or user, and a feature value. A feature may be specifiedas an expression based on values describing the source object or user,the target object or user, or interactions between the source object oruser and target object or user; hence, an edge may be represented as oneor more feature expressions.

The edge store 225 also stores information about edges, such as affinityscores for objects, interests, and other users. Affinity scores, or“affinities,” may be computed by the online system 140 over time toapproximate a user's interest in an object or in another user in theonline system 140 based on the actions performed by the user. A user'saffinity may be computed by the online system 140 over time toapproximate a user's interest in an object, interest in a topic, orinterest in another user in the online system 140 based on actionsperformed by the user. Computation of affinity is further described inU.S. patent application Ser. No. 12/978,265, filed on Dec. 23, 2010,U.S. patent application Ser. No. 13/690,254, filed on Nov. 30, 2012,U.S. patent application Ser. No. 13/689,969, filed on Nov. 30, 2012, andU.S. patent application Ser. No. 13/690,088, filed on Nov. 30, 2012,each of which is hereby incorporated by reference in its entirety.Multiple interactions between a user and a specific object may be storedas a single edge in the edge store 225, in one embodiment.Alternatively, each interaction between a user and a specific object isstored as a separate edge. In some embodiments, connections betweenusers may be stored in the user profile store 205, or the user profilestore 205 may access the edge store 225 to determine connections betweenusers.

The content selection module 230 selects one or more content items forcommunication to a client device 110 to be presented to a user. Contentitems eligible for presentation to the user are retrieved from thecontent store 210 or from another source by the content selection module230, which selects one or more of the content items for presentation tothe viewing user. A content item eligible for presentation to the useris a content item associated with at least a threshold number oftargeting criteria satisfied by characteristics of the user or is acontent item that is not associated with targeting criteria. In variousembodiments, the content selection module 230 includes content itemseligible for presentation to the user in one or more selectionprocesses, which identify a set of content items for presentation to theviewing user. For example, the content selection module 230 determinesmeasures of relevance of various content items to the user based oncharacteristics associated with the user by the online system 140 andbased on the user's affinity for different content items. Based on themeasures of relevance, the content selection module 230 selects contentitems for presentation to the user. As an additional example, thecontent selection module 230 selects content items having the highestmeasures of relevance or having at least a threshold measure ofrelevance for presentation to the user. Alternatively, the contentselection module 230 ranks content items based on their associatedmeasures of relevance and selects content items having the highestpositions in the ranking or having at least a threshold position in theranking for presentation to the user.

Content items selected for presentation to the user may include adrequests or other content items associated with bid amounts. The contentselection module 230 uses the bid amounts associated with ad requestswhen selecting content for presentation to the viewing user. In variousembodiments, the content selection module 230 determines an expectedvalue associated with various ad requests (or other content items) basedon their bid amounts and selects content items associated with a maximumexpected value or associated with at least a threshold expected valuefor presentation. An expected value associated with an ad request orwith a content item represents an expected amount of compensation to theonline system 140 for presenting an ad request or a content item. Forexample, the expected value associated with an ad request is a productof the ad request's bid amount and a likelihood of the user interactingwith the ad content from the ad request. The content selection module230 may rank ad requests based on their associated bid amounts andselect ad requests having at least a threshold position in the rankingfor presentation to the user. In some embodiments, the content selectionmodule 230 ranks both content items not associated with bid amounts andad requests in a unified ranking based on bid amounts associated with adrequests and measures of relevance associated with content items and adrequests. Based on the unified ranking, the content selection module 230selects content for presentation to the user. Selecting ad requests andother content items through a unified ranking is further described inU.S. patent application Ser. No. 13/545,266, filed on Jul. 10, 2012,which is hereby incorporated by reference in its entirety.

For example, the content selection module 230 receives a request topresent a feed of content to a user of the online system 140. The feedmay include one or more advertisements as well as content items, such asstories describing actions associated with other online system usersconnected to the user. The content selection module 230 accesses one ormore of the user profile store 205, the content store 210, the actionlog 220, and the edge store 225 to retrieve information about the user.For example, stories or other data associated with users connected tothe identified user are retrieved. Additionally, one or moreadvertisement requests (“ad requests”) may be retrieved from the contentstore 210. An ad request includes content for presentation to a user aswell as a bid amount indicating a maximum amount of compensationprovided to the online system 140 by an entity associated with the adrequest for presenting the ad request to users or for receiving aninteraction with the ad request. The retrieved stories, ad requests, orother content items, are analyzed by the content selection module 230 toidentify candidate content that is likely to be relevant to theidentified user. For example, stories associated with users notconnected to the identified user or stories associated with users forwhich the identified user has less than a threshold affinity arediscarded as candidate content. Based on various criteria, the contentselection module 230 selects one or more of the content items or adrequests identified as candidate content for presentation to theidentified user. The selected content items or ad requests are includedin a feed of content that is presented to the user. For example, thefeed of content includes at least a threshold number of content itemsdescribing actions associated with users connected to the user via theonline system 140.

In various embodiments, the content selection module 230 presentscontent to a user through a feed including a plurality of content itemsselected for presentation to the user. One or more advertisements mayalso be included in the feed. The content selection module 230 may alsodetermine the order in which selected content items or advertisementsare presented via the feed. For example, the content selection module230 orders content items or advertisements in the feed based onlikelihoods of the user interacting with various content items oradvertisements. When generating a feed, the content selection module 230enforces one or more limitations on content included in the feed in someembodiments. For example, the content selection module 230 limits anumber of video content items or a number of video content items havingspecific characteristics included in a feed. As a specific example, thecontent selection module 230 includes less than a threshold number ofvideo content items associated with advertisers in a feed.

If the content selection module 230 enforces one or more limitations ona number or an amount of video content items included in a feed, thecontent selection module 230 may generate an additional interfaceincluding video content items for presentation to a user who interactswith a video content item presented in the feed. Generating theadditional interface allows the content selection module to provideadditional video content items to a user, which may increase the amountof interaction between the user and content provided by the contentselection module 230 while enforcing limitations on inclusion of videocontent items in the feed. To generate the additional interface, whenthe content selection module 230 receives information indicating a userinteracted with a video content item included in the feed, the contentselection module 230 identifies candidate video content items from thecontent store 210 based on characteristics of the user andcharacteristics of the video content item with which the userinteracted. Candidate video content items have at least a thresholdnumber of characteristics matching characteristics of the user orcharacteristics of the video content item with which the userinteracted. For example, candidate video content items are identified asvideo content items associated with an additional user who provided thevideo content item with which the user interacted to the online system140, video content items associated with the video content item withwhich the user interacted, video content items associated with one ormore interactions associated with the user, video content itemsassociated with a location matching a location associated with the user,or video content items having other suitable characteristics matchingcharacteristics of the user or of the video content item with which theuser interacted. Selection of candidate video content item is furtherdescribed below in conjunction with FIG. 3.

The content selection module 230 determines likelihoods of the userinteracting with various candidate content items. In some embodiments,the content selection module 230 determines a likelihood of the userinteracting with each candidate content item. Alternatively, the contentselection module determines a likelihood of the user interacting witheach candidate content item in a subset of the candidate content item.Various information may be used to determine the likelihood of the userinteracting with a candidate content item. Characteristics of acandidate video content item, characteristics of the user,characteristics of content items with which the user previouslyinteracted, and prior interactions by the user (e.g., prior interactionsby the user with video content items having at least a threshold numberof characteristics matching or similar to characteristics of thecandidate video content item) may be used by a model that the contentselection module 230 applies to the candidate video content item todetermine the likelihood of the user interacting with the candidatevideo content item. The likelihood that a viewing user will interactwith a candidate video content item may also be based on one or moresources from which it was obtained. For example, the scoring module 235identifies sources that are most reliable at predicting the likelihoodthat viewing users will interact with candidate video content items andassociates higher weights with these sources. In some embodiments, thecontent selection module 230 associates different weights with variouscharacteristics of a candidate video content item when determining alikelihood of the user interacting with the candidate video contentitem; for example, higher weights are associated with characteristics ofthe candidate video content item matching characteristics of the videocontent item with which the user interacted.

Based at least in part on the likelihoods of the user interacting withvarious candidate content items, the content selection module 230selects one or more candidate content items and generates an interfaceincluding the selected candidate content items. For example, the contentselection module 230 ranks the candidate content items based on theirassociated likelihoods of user interaction and selects candidate contentitems having at least a threshold likelihood being interacted with bythe user. Alternatively, the content selection module 230 selectscandidate content items having at least a threshold likelihood of beinginteracted with by the user. In some embodiments, the content selectionmodule selects candidate video content items and other types of contentitems for inclusion in the interface based on the likelihoods of theuser interacting with various candidate video content items andlikelihoods of the user interacting with other types of content items.The generated interface is communicated for a client device 110associated with the user for presentation, allowing the user to view andinteract with the selected candidate video content items. In someembodiments, the generated interface is a content presentation unitpresented in a feed generated by the content selection module 230, andas the user interacts with the content presentation unit, a differentselected candidate content item is presented by the content presentationunit. Alternatively, the generated interface is a different feedincluding the selected candidate video content items that is presentedto the user. Examples of interfaces including selected candidate videocontent items are further described below in conjunction with FIGS.4A-4B.

The web server 235 links the online system 140 via the network 120 tothe one or more client devices 110, as well as to the one or more thirdparty systems 130. The web server 235 serves web pages, as well as othercontent, such as JAVA®, FLASH®, XML and so forth. The web server 235 mayreceive and route messages between the online system 140 and the clientdevice 110, for example, instant messages, queued messages (e.g.,email), text messages, short message service (SMS) messages, or messagessent using any other suitable messaging technique. A user may send arequest to the web server 235 to upload information (e.g., images orvideos) that is stored in the content store 210. Additionally, the webserver 235 may provide application programming interface (API)functionality to send data directly to native client device operatingsystems, such as IOS®, ANDROID™, WEBOS®, or BlackberryOS.

Presenting Video Content Items Responsive to User Interactions with aVideo Content Item

FIG. 3 is a flowchart of one embodiment of a method for presentingadditional video content items to an online system user responsive toreceiving an interaction by the user with a video content item presentedby the online system 140. In other embodiments, the method may includedifferent and/or additional steps than those shown in FIG. 3.Additionally, steps of the method may be performed in different ordersthan the order described in conjunction with FIG. 3 in variousembodiments.

The online system 140 generates 305 a feed of content items forpresentation to a user that includes one or more content items includingvideo data (“video content items”). For example, the online system 140generates 305 the feed in response to receiving a request from the userfor content. For example, the online system 140 generates 305 the feedafter receiving a request to a request to refresh a feed of content forthe user or after receiving a request for a feed of content item fromthe user. When generating 305 the feed, the online system 140 enforcesone or more limitations on inclusion of video content items in the feed.For example, the online system includes no more than a threshold numberof video content items in the feed or includes no more than a thresholdnumber of video content items having one or more specificcharacteristics in the feed. The online system 140 presents 310 thegenerated feed to the user. For example, the online system 140communicates the generated feed to a client device 110 associated withthe user for presentation 310.

When the user interacts with a video content item included in the feed,the online system 140 receives 315 information describing theinteraction with the video content item. Example interactions with thevideo content item include: requesting to play video data included inthe video content item (e.g., accessing an interface element or adisplay area of the video data), unmuting the video data in the videocontent item (e.g., if the video data automatically plays, aninteraction increasing volume of the video data), increasing the volumeof the video data in the video content item to greater than a thresholdlevel, requesting presentation of the video data in the video contentitem in a larger display area (e.g., presenting the video data in adisplay area occupying at least a threshold amount of a display area ofa client device 110), and presenting at least a threshold percentage ofthe video data in the video content item (e.g., presenting at least 51%of the video data in the video content item). Information received 315by the online system describing the interaction with the video contentitem identifies the video content item and may also identify the type ofinteraction with the video content item.

Responsive to receiving 310 the information describing the interactionby the user with the video content item included in the feed, the onlinesystem 140 retrieves 320 candidate content items based oncharacteristics of the user or characteristics of the video content itemwith which the user interacted. The online system 140 retrieves 320candidate video content items having that have at least a thresholdnumber of characteristics matching characteristics of the video contentitem with which the user interacted or having at least a thresholdnumber of characteristics matching characteristics of the user. Forexample, the online system 140 retrieves 320 video content itemsprovided to the online system 140 by a user who provided the videocontent item with which the user interacted as candidate video contentitems. As another example, the online system 140 retrieves 320 candidatevideo content items that are video content items including text data(e.g., keywords, hashtags) matching (or associated with) text dataincluded in the video content item with which the user interacted.Additionally, video content items associated with the video content itemwith which the viewing user interacted (e.g., additional video contentitems posted in comments to the video content item, additional videocontent items manually linked to the video content item, additionalvideo content items associated with one or more actions performed by theuser on a third party system and communicated to the online system,etc.) may be retrieved 320 as candidate video content items. In anotherexample, video content items having at least a threshold measure ofsimilarity to video content items with which the user previouslyinteracted are retrieved 320 as candidate content items (e.g., videocontent items having at least a threshold number of characteristicsmatching characteristics of a video content item with which the userpreviously performed a specific interaction).

In various embodiments, the online system 140 retrieves 320 one or morecandidate video content items having characteristics matching at least athreshold number of characteristics associated with the user. Forexample, video content items associated with a geographic location (orother demographic information, such as an interest) matching ageographic location (or other demographic information, such as aninterest) associated with the user are retrieved 320 as candidate videocontent items. As another example, video content items that areassociated with an interaction or action that is also associated withthe user (e.g., video content items associated with a prior searchperformed by the user via the online system) are retrieved 320 ascandidate video content items. Characteristics of the user may includemeasures of similarity between the user and additional users of theonline system 140. For example, the online system 140 generates ameasure of similarity between a user and an additional user based onmatching or similar characteristics of the user and the additional user,content with which the user and the additional user interacted, or othersuitable information. Video content items with which additional usershaving at least a threshold measure of similarity to the user interactedare retrieved 320 as candidate video content items in some embodiments.For example, additional video content items with which additional usershaving at least a threshold measure of similarity to the user and whoperformed a specific action (e.g., posted the additional video contentitem to the online system, shared the additional video content item withanother user, viewed video data in the additional video content item,commented on the additional video content item etc.) are retrieved 320as candidate video content items.

The online system 140 determines 325 likelihoods of the user interactingwith various candidate video content items based on characteristics ofthe user, characteristics of the candidate video content items, priorinteractions by the user, or any other suitable information. Forexample, the online system 140 determines 325 a likelihood of the userinteracting with a candidate video content item based on priorinteractions by the user with video content items having at least athreshold number of characteristics or having at least a thresholdmeasure of similarity to the candidate video content item. In someembodiments, the online system 140 applies a model to a video contentitem that associates weights with various characteristics of the videocontent item to determine 325 a likelihood of the user interacting withthe candidate video content item. The online system 140 may modifyweights associated with characteristics of candidate video items overtimes based on interactions by the user with candidate video contentitems that are presented to the user to improve accuracy of thedetermination of the likelihood of the user interacting with candidatevideo content items. For example, if 90% of the user's previousinteractions with video content items were with video content itemsprovided to the online system 140 by additional users to which the useris connected, the online system 140 increases a weight applied to acharacteristic of video content items indicating the video content itemswere provided to the online system 140 when determining 325 likelihoodsof the user interacting with the video content items. The online system140 may associate different models with different users and use a modelassociated with the user to determine 325 the likelihoods of the userinteracting with the candidate content items to more accuratelydetermine 325 the likelihoods.

In some embodiments, the online system 140 determines 325 likelihoods ofthe user interacting with each candidate video content item.Alternatively, the online system 140 determines 325 likelihoods of theuser interacting with each of a subset of the candidate video contentitems. For example, the online system 140 identifies candidate videocontent items having one or more characteristics and determines 325likelihoods of the user interacting with each of the identifiedcandidate video content items. In some embodiments, the online system140 identifies candidate video content items having greater than athreshold number of characteristics matching characteristics of the useror characteristics of the video content item with which the userinteracted and determines 325 likelihoods of the user interacting witheach of the identified candidate video content items.

Based at least in part on the likelihoods of the user interacting withthe candidate video content items, the online system 140 selects 330 oneor more candidate video content items. For example, the online system140 ranks the candidate video content items based on their associatedlikelihoods of being interacted with by the user and selects 330candidate video content items having at least a threshold position inthe ranking. Alternatively, the online system 140 selects 330 candidatevideo content items having at least a threshold likelihood of beinginteracted with by the user. In some embodiments, the online system 140selects 330 candidate video content items as well as other types ofcontent items based on the likelihoods of the user interacting with thecandidate video content items and based on the likelihoods of the userinteracting with the other types of content items (e.g., content itemsincluding text data, content items including image data, etc.).Likelihoods of the user interacting with other types of content itemsare determined similarly to the likelihoods of the user interacting withthe candidate video content items. For example, the online system 140selects at least a threshold number of other types of content items aswell as candidate video content items. For example, the online system140 enforces a limitation restricting a number or percentage ofnon-video content items that are selected 330, so less than the numberor percentage of non-video content items are selected 330. In someembodiments, the online system 140 separately selects 330 candidatevideo content items and other types of content items; alternatively, theonline system 140 includes both candidate video content items and othertypes of content items in a single selection process.

The online system 140 generates 335 an interface including the selectedcandidate video content items. The generated interface may be configuredto present the selected candidate video content items in a variety offormats in various embodiments. For example, the generated interface isa separate feed including the selected candidate video content items.Alternatively, the generated interface is a content presentation unitincluded in the feed presented to the user. The content presentationunit presents a single selected video candidate content item, butpresents a different selected video candidate content item in responseto certain user interactions with the content presentation unit. Forexample, if the feed presents content items in a vertical list andincludes a content presentation unit, when certain interactions with thecontent presentation unit are received, the content presentation unithorizontally scrolls to present an alternative selected candidatecontent item. In some embodiments, the generated interface groupsselected candidate video content items based on characteristics of thecandidate video content items matching characteristics of the user orcharacteristics of the video content item with which the userinteracted. For example, a group of selected candidate video contentitems in the generated interface includes selected candidate videocontent items having a characteristic matching a specific characteristicof the video content item with which the user interacted, while anothergroup of selected candidate video content item includes selectedcandidate video content items having a characteristic matching aspecific characteristic of the user. Examples of the generated interfaceare further described below in conjunction with FIGS. 4A-4C. The onlinesystem 140 presents 340 the generated interface to the user, allowingthe user to view and interact with the selected candidate video contentitems. For example, the online system 140 communicates the generatedinterface to a client device 110 associated with the user forpresentation.

FIG. 4A is an example interface including candidate video content itemsselected by an online system 140 for presentation to a user. In theexample of FIG. 4A, the online system 140 provides a feed 400 includingcontent items 405A-405D that do not include video data and also includesless than a threshold number of video content items. When the userinteracts with a video content item included in the feed 400, the onlinesystem 140 selects candidate video content items to present to the userand generates an interface including the selected candidate videocontent items, as described above in conjunction with FIG. 3. To presentthe selected candidate video content items without violating limitationson the number of video content items included in the feed, the onlinesystem 140 generates an interface that is a content presentation unit410 including multiple selected candidate video content items 415A,415B, 415C. The content presentation unit 410 may include content itemsother than selected candidate video content items 410 (e.g., contentitems including text or image data and not video data) in someembodiments. Additionally, information describing one or more reasonsfor inclusion of selected candidate video content items 415 in thecontent presentation unit 410 may be presented along with the selectedcandidate video content items 415 in the content presentation unit 410(e.g., characteristics of a selected candidate video content item 415matching a video content item with which the user interacted,characteristics of a selected video content item 415 matchingcharacteristics of the user).

As shown in FIG. 4A, the content presentation unit 410 is presented inthe feed 400 of content and presents a single selected candidate videocontent item 415A in the feed 400. However, when the user performscertain interactions with the content presentation unit 410, the contentpresentation unit 410 presents a different selected candidate videocontent item 415B, 415C in the feed 400, increasing the number of videocontent items the user may view in the feed 400 while maintaining one ormore limitations on the number of video content items presented in thefeed 400. For example, if the user performs one or more gestures with aregion of a display device presenting the content presentation unit 410(e.g., a gesture moving horizontally across the region of the displaydevice) or interacts with a specific interface element in the contentpresentation unit 410 (e.g., a scroll bar or a navigation button), adifferent selected candidate video content item 415B, 415C is displayedin the feed 400 by the content presentation unit 410. Alternatively, thecontent presentation unit 410 presents a different selected candidatevideo content item 415B, 415C when the selected candidate video contentitem 415A presented in the feed 400 by the content presentation unit 410completely plays. As another embodiment, the content presentation unit410 changes presented information describing selected candidate videocontent items 415 at various time intervals and presents a selectedcandidate video content item 415 associated with information presentedby the content presentation unit when an interaction with the contentpresentation unit 410 is received. In some embodiments, the contentpresentation unit 410 returns to the candidate video content item 415Ainitially presented in the content presentation unit 410 afterpresenting a threshold number of candidate video content items 415;alternatively, the content presentation unit returns to the candidatevideo content item 415A in response to receiving user interactions(e.g., interactions requesting navigation through candidate videocontent items 415 to the candidate video content item 415A that wasinitially presented).

In the example of FIG. 4B, the online system 140 generates an interfacethat is an additional feed 420 including selected candidate videocontent items 415A-415D in response to receiving an interaction with theuser by a video content item 407 included in the feed 400 along withother content items 405A-405D. The additional feed 420 may be presentedto the user in addition to the feed 400 or in place of the feed 400 invarious embodiments. In some embodiments, the additional feed 420includes the selected candidate video content items as well as othertypes of content items (e.g., content items including text data or imagedata and not including video data). Additionally, the additional feed420 may include information associated with various selected candidatevideo content items 415A-415D specifying one or more reasons forinclusion of the candidate video content items 415A-415D in theadditional feed, as described above in conjunction with FIG. 4A.

FIG. 4C shows another example of the interface where selected candidatevideo content items 415A-415D are presented in a channel 430 that playsthe candidate video content items 415A-415D in a sequence. In theexample of FIG. 4C, the channel 430 initially plays a selected candidatevideo content item 415A then plays selected video content items415B-415D in series after candidate video content item 415A hascompleted playing. In some embodiments, the sequence in which theselected video content items 415A-415D are played is based at least inpart on the likelihoods of the user interacting with various selectedvideo content items 415A-415D, so selected candidate video content items415A-415D with which the user is more likely to interact have earlierpositions in the sequence. The channel 430 is presented to the user inresponse to the user interacting with a video content item 407 includedin a feed 400 of content items 405A-405D presented to the user. In someembodiments, the channel 430 includes selected candidate video contentitems 415A-415D having a common characteristic (e.g., a specificcharacteristic matching a characteristic of the user or a characteristicof the video content item 407 included in the feed), and the onlinesystem 140 generates different channels 430 for differentcharacteristics. As described above in conjunction with FIGS. 4A and 4B,additional information may be presented in the channel 430 inassociation with the selected candidate video content items 415A-415D.

SUMMARY

The foregoing description of the embodiments has been presented for thepurpose of illustration; it is not intended to be exhaustive or to limitthe patent rights to the precise forms disclosed. Persons skilled in therelevant art can appreciate that many modifications and variations arepossible in light of the above disclosure.

Some portions of this description describe the embodiments in terms ofalgorithms and symbolic representations of operations on information.These algorithmic descriptions and representations are commonly used bythose skilled in the data processing arts to convey the substance oftheir work effectively to others skilled in the art. These operations,while described functionally, computationally, or logically, areunderstood to be implemented by computer programs or equivalentelectrical circuits, microcode, or the like. Furthermore, it has alsoproven convenient at times, to refer to these arrangements of operationsas modules, without loss of generality. The described operations andtheir associated modules may be embodied in software, firmware,hardware, or any combinations thereof.

Any of the steps, operations, or processes described herein may beperformed or implemented with one or more hardware or software modules,alone or in combination with other devices. In one embodiment, asoftware module is implemented with a computer program productcomprising a computer-readable medium containing computer program code,which can be executed by a computer processor for performing any or allof the steps, operations, or processes described.

Embodiments may also relate to an apparatus for performing theoperations herein. This apparatus may be specially constructed for therequired purposes, and/or it may comprise a general-purpose computingdevice selectively activated or reconfigured by a computer programstored in the computer. Such a computer program may be stored in anon-transitory, tangible computer readable storage medium, or any typeof media suitable for storing electronic instructions, which may becoupled to a computer system bus. Furthermore, any computing systemsreferred to in the specification may include a single processor or maybe architectures employing multiple processor designs for increasedcomputing capability.

Embodiments may also relate to a product that is produced by a computingprocess described herein. Such a product may comprise informationresulting from a computing process, where the information is stored on anon-transitory, tangible computer readable storage medium and mayinclude any embodiment of a computer program product or other datacombination described herein.

Finally, the language used in the specification has been principallyselected for readability and instructional purposes, and it may not havebeen selected to delineate or circumscribe the inventive subject matter.It is therefore intended that the scope of the patent rights be limitednot by this detailed description, but rather by any claims that issue onan application based hereon. Accordingly, the disclosure of theembodiments is intended to be illustrative, but not limiting, of thescope of the patent rights, which is set forth in the following claims.

1. A method comprising: generating a feed of content items for a user of an online system, the feed including one or more video content items each presented in a separate horizontally scrollable content presentation unit, a number of the one or more video content items in the feed being subject to a restriction on a number of video content items included in the feed; providing the generated feed to a client device for presentation to the user; responsive to receiving information describing one or more interactions by the user with a video content item in a content presentation unit included in the feed, retrieving information describing a plurality of candidate video content items maintained by the online system, each candidate video content item having at least a threshold number of characteristics matching characteristics of the video content item; determining likelihoods of the user interacting with each of the candidate video content items based at least in part on characteristics of the user and characteristics of the candidate video content items; selecting one or more of the candidate video content items based at least in part on the determined likelihoods; and presenting one of the selected candidate video content items in the content presentation unit to the user, the content presentation unit able to scroll in a direction perpendicular to the feed to present a different selected candidate video content item.
 2. The method of claim 1, wherein retrieving information describing a plurality of candidate video content items maintained by the online system comprises: retrieving information describing one or more candidate video content items having at least the threshold number of characteristics matching characteristics of the video content item; and retrieving information describing one or more candidate video content items having at least a threshold number of characteristics matching characteristics of the user.
 3. The method of claim 2, wherein a characteristic of the user comprises measures of similarity between the user and one or more additional users of the online system.
 4. The method of claim 3, wherein retrieving information describing one or more candidate video content items having at least a threshold number of characteristics matching characteristics of the user comprises: retrieving information describing one or more candidate video content items associated with an additional user with whom the user has at least a threshold measure of similarity.
 5. The method of claim 2, wherein a characteristic of the user is selected from a group consisting of: a geographic location associated with the user, an interest associated with the user, and any combination thereof.
 6. The method of claim 1, wherein a characteristic of the video content item is selected from a group consisting of: a user who provided the video content item to the online system, text data included in the video content item, an association between the video content item and a candidate video content item, and any combination thereof.
 7. (canceled)
 8. The method of claim 1, wherein the content presentation able to scroll in a direction perpendicular to the feed comprises: displaying one or more additional selected candidate content items in response to a user interaction with the content presentation unit.
 9. The method of claim 1, wherein the restriction on the number of video content items included in the feed comprises a maximum number of video content items included in the feed.
 10. The method of claim 1, wherein the restriction on the number of video content items included in the feed comprises a maximum number of video content items having one or more specified characteristics included in the feed.
 11. The method of claim 1, wherein selecting one or more of the candidate video content items based at least in part on the determined likelihoods comprises: ranking the candidate video content items based at least in part on the determined likelihoods; and selecting candidate video content items having at least a threshold position in the ranking.
 12. The method of claim 1, wherein selecting one or more of the candidate video content items based at least in part on the determined likelihoods comprises: selecting one or more candidate video content items having at least a threshold determined likelihood of being interacted with by the user.
 13. The method of claim 1, wherein determining likelihoods of the user interacting with each of the candidate video content items based at least in part on characteristics of the user and characteristics of the candidate video content items comprises: associating weights with characteristics of a candidate video content item; and determining a likelihood of the user interacting with the candidate video content item based at least in part on the weights, the characteristics of the candidate video content item, and the characteristics of the user.
 14. The method of claim 1, wherein an interaction by the user with the video content item included in the feed is selected from a group consisting of: requesting to play video data included in the video content item included in the feed, unmuting video data in the video content item included in the feed, increasing a volume of video data in the video content item included in the feed to greater than a threshold level, requesting presentation of the video data in the video content item included in the feed a larger display area occupying at least a threshold amount of a display area of a client device, presenting at least a threshold percentage of video data in the video content item included in the feed, and any combination thereof.
 15. A computer program product comprising a non-transitory computer-readable storage medium having instructions encoded thereon that, when executed by a processor, cause the processor to: generate a feed of content items for a user of an online system, the feed including one or more video content items each presented in a separate horizontally scrollable content presentation unit, a number of the one or more video content items in the feed being subject to a restriction on a number of video content items included in the feed; provide the generated feed to a client device for presentation to the user; responsive to receiving information describing one or more interactions by the user with a video content item in a content presentation unit included in the feed, retrieve information describing a plurality of candidate video content items maintained by the online system, each candidate video content item having at least a threshold number of characteristics matching characteristics of the video content item; determine likelihoods of the user interacting with each of the candidate video content items based at least in part on characteristics of the user and characteristics of the candidate video content items; select one or more of the candidate video content items based at least in part on the determined likelihoods; and present one of the selected candidate video content items in the content presentation unit to the user, the content presentation unit able to scroll in a direction perpendicular to the feed to present a different selected candidate video content item.
 16. The computer program product of claim 15, wherein retrieve information describing a plurality of candidate video content items maintained by the online system comprises: retrieve information describing one or more candidate video content items having at least the threshold number of characteristics matching characteristics of the video content item; and retrieve information describing one or more candidate video content items having at least a threshold number of characteristics matching characteristics of the user.
 17. (canceled)
 18. The computer program product of claim 15, wherein the content presentation able to scroll in a direction perpendicular to the feed generate the interface including the selected candidate video content items comprises: display one or more additional selected candidate content items in response to a user interaction with the content presentation unit.
 19. The computer program product of claim 15, wherein the restriction on the number of video content items included in the feed comprises a maximum number of video content items included in the feed.
 20. The computer program product of claim 15, wherein an interaction by the user with the video content item included in the feed is selected from a group consisting of: requesting to play video data included in the video content item included in the feed, unmuting video data in the video content item included in the feed, increasing a volume of video data in the video content item included in the feed to greater than a threshold level, requesting presentation of the video data in the video content item included in the feed a larger display area occupying at least a threshold amount of a display area of a client device, presenting at least a threshold percentage of video data in the video content item included in the feed, and any combination thereof. 